I’ve been working on image classification and segmentation quite a lot recently, and totally in love with GPU big data processing. If you wanna process data that at gigabyte (G) level data definitely look into start a GPU AWS instance 最近我的工作接触了很多图像分类，和图像分割的内容，感觉自己太爱gpu图像分析的世界：太神速了。如果你现在处理的数据已经达到G级别了，我觉得你还是应该开一个亚马逊的ami（亚马逊的深度学习平台／机器）

It is not free, though. You definitely would start with AWS free tier, but I normally use their g or p machines. For example, if I use g2.2 x large, I will be charged about $0.65 per hour. for more information, go here. It charges by how much you use and if you are new to deep learning and just wanna run some case studies, I think it worths more than building your own GPU machine or buy a new pc with super GPU.

What do you wanna do with the AWS machine? Do you wanna learn just some basic machine learning stuffs that you only need to process megabyte (?M) level csv/txt data file you could just use your personal computer. A personal computer is fast enough though days. 你想拿这个亚马逊深度学习平台来做什么？如果只是用来处理几兆几十兆的数据的话，那还是没有必要开一个，现在的个人电脑那么快完全可以处理这些数据了。

As I mentioned above, if you wanna process images or data that above some certain level your personal computer could not handle. Think about how much you wanna spend on the data processing. Again, evaluate your situation, needs and do some research. 但是，如果你的数据量已经是在几百兆或者g级别的，当然还是很有必要开一个的。话说回来，还是应该做些调查研究加上考量自己的情况。

A machine that has Tensorflow, Theano, Torch, Keras, and also Caffe installed. Tensorflow, Theano, Torch, and Caffe are deep learning ecosystem/environment. Keras is the python module that I use to build deep learning algorithm architecture.想这个ami机器上有我想用的几个深度学习框架，比如Tensorflow, Theano, Torch, and Caffe。还有如果有keras，python的一个构建深度学习／机器学习的包。